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Combinatorial Optimization

Combinatorial Optimization is a category of problems which requires optimizing a function over a combination of discrete objects and the solutions are constrained. Examples include finding shortest paths in a graph, maximizing value in the Knapsack problem and finding boolean settings that satisfy a set of constraints. Many of these problems are NP-Hard, which means that no polynomial time solution can be developed for them. Instead, we can only produce approximations in polynomial time that are guaranteed to be some factor worse than the true optimal solution.

Source: Recent Advances in Neural Program Synthesis

Papers

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Showing 51–100 of 1277 papers

TitleStatusHype
Denoising Autoencoders for fast Combinatorial Black Box OptimizationCode1
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural NetworksCode1
A Fast Task Offloading Optimization Framework for IRS-Assisted Multi-Access Edge Computing SystemCode1
HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMsCode1
Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems like Max-CutCode1
Incremental Sampling Without Replacement for Sequence ModelsCode1
Contingency-Aware Influence Maximization: A Reinforcement Learning ApproachCode1
JoinGym: An Efficient Query Optimization Environment for Reinforcement LearningCode1
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on GraphsCode1
Large Language Models as Evolutionary OptimizersCode1
A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial OptimizationCode1
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop SchedulingCode1
DataSculpt: Crafting Data Landscapes for Long-Context LLMs through Multi-Objective PartitioningCode1
DHRL-FNMR: An Intelligent Multicast Routing Approach Based on Deep Hierarchical Reinforcement Learning in SDNCode1
Equivariant quantum circuits for learning on weighted graphsCode1
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree SearchCode1
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable ApproachCode1
Combinatorial Optimization with Physics-Inspired Graph Neural NetworksCode1
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial OptimizationCode1
A Learning-based Iterative Method for Solving Vehicle Routing ProblemsCode1
Belief Propagation Neural NetworksCode1
BILP-Q: Quantum Coalition Structure GenerationCode1
CLIPPER: A Graph-Theoretic Framework for Robust Data AssociationCode1
Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement LearningCode1
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time WindowsCode1
Combinatorial Optimization Perspective based Framework for Multi-behavior RecommendationCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
A Bayesian algorithm for retrosynthesisCode1
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman ProblemCode1
Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent setCode1
D2Match: Leveraging Deep Learning and Degeneracy for Subgraph MatchingCode1
DeepACO: Neural-enhanced Ant Systems for Combinatorial OptimizationCode1
Deep Boltzmann Machines in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
Automatic Truss Design with Reinforcement LearningCode1
Deep Graph Matching via Blackbox Differentiation of Combinatorial SolversCode1
Active Learning Meets Optimized Item SelectionCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionCode1
A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with DroneCode1
DIMES: A Differentiable Meta Solver for Combinatorial Optimization ProblemsCode1
Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial OptimizationCode1
Attention, Learn to Solve Routing Problems!Code1
ASP: Learn a Universal Neural Solver!Code1
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization SolversCode1
An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint ProgrammingCode1
Quantum approximate optimization via learning-based adaptive optimizationCode1
Exploring the Power of Graph Neural Networks in Solving Linear Optimization ProblemsCode1
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization AlgorithmsCode1
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task AllocationCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionsCode1
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